LLM Comparison

GPT-6 Astra vs DeepSeek V4 Pro 0813: benchmark scores, pricing & comparison.

Side-by-side GPT-6 Astra vs DeepSeek V4 Pro 0813 comparison across SWE-bench, GPQA, HLE, Terminal-Bench, coding agent scores, token pricing, context window, and AskClash RWT. Green marks the winner on each benchmark.

Rank #7 vs #28AskClash overall scores 64.9 vs 52.9.
Pricing $10.0/$50.0 vs $0.43/$0.87Input and output token prices per 1M tokens when published.
Proprietary vs Open WeightOpenAI vs DeepSeek.

GPT-6 Astra vs DeepSeek V4 Pro 0813 benchmark comparison

Green cells highlight the winning model for each metric. Scores are cached from the AskClash LLM leaderboard snapshot.

MetricGPT-6 AstraDeepSeek V4 Pro 0813
Overall Score64.952.9
Leaderboard Rank#7#28
ACB54.8
RWT9.57.0
Coding Agent Index67.0
HLE57.242.7
GPQA96.090.1
SWE-bench80.6
SWE-Pro55.4
Terminal-Bench87.9
DeepSWE74.162.7
GDPval-AA1554.0
MCP Atlas73.6
Finance Agent44.1
ARC-AGI 295.0
Tau296.2
MRCR100.0
Input Price (per 1M tokens)$10.0$0.43
Output Price (per 1M tokens)$50.0$0.87
Context Window1M1M
Benchmarks Published711

GPT-6 Astra vs DeepSeek V4 Pro 0813 head-to-head charts

GPT-6 Astra leads 5 and DeepSeek V4 Pro 0813 leads 0 of 5 shared benchmarks. DeepSeek V4 Pro 0813 is cheaper on a defined 1M-input / 200K-output workload. Charts show only benchmarks both models publish.

GPT-6 AstraDeepSeek V4 Pro 0813
Overall
64.9GPT-6 Astra
52.9DeepSeek V4 Pro 0813
RWT
9.5GPT-6 Astra
7.0DeepSeek V4 Pro 0813
HLE
57.2GPT-6 Astra
42.7DeepSeek V4 Pro 0813
GPQA
96.0GPT-6 Astra
90.1DeepSeek V4 Pro 0813
DeepSWE
74.1GPT-6 Astra
62.7DeepSeek V4 Pro 0813
GPT-6 Astra
Input$10.0
Output$50.0
Workload$20
Context1M
DeepSeek V4 Pro 0813
Input$0.43
Output$0.87
Workload$0.61
Context1M

Workload = published cost of 1M input + 200K output tokens. Open the live leaderboard for interactive compare charts.

More GPT-6 Astra and DeepSeek V4 Pro 0813 comparisons

Explore how GPT-6 Astra and DeepSeek V4 Pro 0813 stack up against other top-ranked LLMs.

How to read this comparison

Benchmark scores

Higher is better for all benchmark scores (SWE-bench, GPQA, HLE, Terminal-Bench, etc.). Green marks the model with the higher score.

Token pricing

Lower is better for input and output prices. Green marks the cheaper model per 1M tokens.

Coverage matters

Models with fewer disclosed benchmark cells may have inflated percentile scores. Check the benchmark cell count for context.

This comparison page is generated from the AskClash LLM leaderboard cache. Open the live leaderboard for real-time scores and interactive filtering.